An exact bound for tail probabilities for a class of conditionally symmetric bounded martingales

Dainius Dzindzalieta
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Abstract

We consider the class, say ℳn,sym, of martingales Mn = X1 + ⋯ + Xn with conditionally symmetric bounded differences Xk such that |Xk | ≤ 1. We find explicitly a solution, say Dn(x), of the variational problem Dn(x) ≝ sup Mn ∈ℳn,sym ℙ {Mn ≥ x}. We show that this problem is equivalent to one when you want to find out the symmetric random walk with bounded length of steps which maximizes the probability to visit an interval [x;∞]. The function x \mapsto Dn(x) allows a simple description and is closely related to the binomial tail probabilities. We can interpret the result as a final and optimal upper bound ℙ{Mn ≥ x} ≤ Dn(x), x ∈ ℝ, for the tail probability ℙ {Mn ≥ x}.
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一类条件对称有界鞅的尾概率的精确界
我们考虑一类鞅Mn = X1 +⋯+ Xn,sym,具有条件对称有界差分Xk,使得|Xk |≤1。我们显式地找到变分问题Dn(x)的一个解,例如Dn(x) exists sup Mn∈n,sym {Mn≥x}。我们证明,当你想找出具有有限步长的对称随机漫步,使访问区间[x;∞]的概率最大化时,这个问题等价于一个问题。函数x \mapsto Dn(x)允许一个简单的描述,并且与二项尾部概率密切相关。我们可以将结果解释为尾概率(tail probability)的最终最优上界(≤Dn(x), x∈x)。
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